Pure CuBi2O4 Photoelectrodes with Increased Stability by Rapid Thermal Processing of Bi2O3/CuO Grown by Pulsed Laser Deposition

A new method for enhancing the charge separation and photo‐electrochemical stability of CuBi₂O₄ photoelectrodes by sequentially depositing Bi₂O₃ and CuO layers on fluorine‐doped tin oxide substrates with pulsed laser deposition (PLD), followed by rapid thermal processing (RTP), resulting in phase‐pure, highly crystalline films after 10 min at 650 °C, is reported. Conventional furnace annealing of similar films for 72 h at 500 °C do not result in phase‐pure CuBi₂O₄. The combined PLD and RTP approach allow excellent control of the Bi:Cu stoichiometry and results in photoelectrodes with superior electronic properties compared to photoelectrodes fabricated through spray pyrolysis. The low photocurrents of the CuBi₂O₄ photocathodes fabricated through PLD/RTP in this study are primarily attributed to their low specific surface area, lack of CuO impurities, and limited, slow charge transport in the undoped films. Bare (without protection layers) CuBi₂O₄ photoelectrodes made with PLD/RTP shows a photocurrent decrease of only 26% after 5 h, which represents the highest stability reported to date for this material. The PLD/RTP fabrication approach offers new possibilities of fabricating complex metal oxides photoelectrodes with a high degree of crystallinity and good electronic properties at higher temperatures than the thermal stability of glass‐based transparent conductive substrates would allow.     

Tracking Twin Boundary Jerky Motion at Nanometer and Microsecond Scales

The jerky motion of twin boundaries in the ferromagnetic shape memory alloy Ni-Mn-Ga is studied by simultaneous measurements of stress and magnetic emissions (ME). A careful design of the experimental conditions results in an approximately linear relationship between the measured ME voltage and the nm-scale volumes exhibiting twinning transformation during microsecond-scale abrupt “avalanche” events. This study shows that the same distributions of ME avalanches, related to features of jerky twin boundary motion, are found both during and between stress drop events. Maximum likelihood analysis of statistical distributions of several variables reveals a good fit to power laws truncated by exponential functions. Interestingly, the characteristic cutoffs described by the exponential functions are in the middle of the distribution range. Further, the cutoff values can be related to the physical characteristics of the studied problem. Particularly, the cutoff of amplitudes of ME avalanches matches the value predicted by high rate magnetic pulse tests performed under much larger driving force values. This observation implies that avalanches during slow rate twin boundary motion and velocity changes observed by high rate tests represent the same behavior and can be described by the same theory.     

A multi-layer sampler for the study of detailed hydrochemical profiles in groundwater

A modular multi-layer sampler was developed and utilized for sampling undisturbed groundwater chemical profiles. Sampling at 3 cm depth intervals is based on the dialysis-cell method and has no depth limitations. The sampler may be used for water quality monitoring and research, both in existing or specially drilled screened wells     

A complete characterization of statistical query learning with applications to evolvability

Statistical query (SQ) learning model of Kearns is a natural restriction of the PAC learning model in which a learning algorithm is allowed to obtain estimates of statistical properties of the examples but cannot see the examples themselves (Kearns, 1998 [29]). We describe a new and simple characterization of the query complexity of learning in the SQ learning model. Unlike the previously known bounds on SQ learning (Blum, et al., 1994; Bshouty and Feldman, 2002; Yang, 2005; Balcázar, et al., 2007; Simon, 2007 [9], [11], [42], [3], [37]) our characterization preserves the accuracy and the efficiency of learning. The preservation of accuracy implies that our characterization gives the first characterization of SQ learning in the agnostic learning framework of Haussler (1992) [23] and Kearns, Schapire and Sellie (1994) [31]. The preservation of efficiency is achieved using a new boosting technique and allows us to derive a new approach to the design of evolution algorithms in Valiant?s model of evolvability (Valiant, 2009 [40]). We use this approach to demonstrate the existence of a large class of monotone evolution algorithms based on square loss performance estimation. These results differ significantly from the few known evolution algorithms and give evidence that evolvability in Valiant?s model is a more versatile phenomenon than there had been previous reason to suspect.     

Equipment for complex tuning and calibration of instruments for the measurement of the time characteristics of optical pulses

Equipment for complex tuning and calibration of instruments used in the measurement of the time characteristics of optical pulse radiation in the nano- and pico-second range is described. Results of calibration of an optoelectronic camera with scanning rates in the range (1.1–9.6)·10⁶ m/sec are presented.     

A signal decomposition or lowpass filtering with Hilbert transform?

Recently, Chen and Wang discovered an explicit formula that makes use of the Hilbert transform for accurate decomposition of a lower harmonic from a signal composition. This letter presents another proof with a new interpretation for the formula using the Bedrosian identity for overlapping signals. This new and simpler proof is based only on the Hilbert transform and does not involve presentation of the Fourier transform. As a result the discovered formula is introduced as a lowpass filter suitable for non-stationary signals.     

Decomposition of non-stationary signals into varying time scales: Some aspects of the EMD and HVD methods

The Empirical Mode Decomposition has become very popular since its first introduction. Its suitability and expected performance for specific signal processing task is however somewhat open ended.Addressed are basic questions concerning the decomposition of signals according to different time scales, from noise sensitivity to frequency resolution. Comparing it to the recently introduced Hilbert Vibration Decomposition, signals simulating moving mechanical systems are analyzed. It is argued that in spite of signal adaptive properties, a universal fully automatic decomposition is still beyond our capabilities.     

Adhesion and Surface Interactions of a Self‐Healing Polymer with Multiple Hydrogen‐Bonding Groups

The surface properties and self‐adhesion mechanism of self‐healing poly(butyl acrylate) (PBA) copolymers containing comonomers with 2‐ureido‐4[1H]‐pyrimidinone quadruple hydrogen bonding groups (UPy) are investigated using a surface forces apparatus (SFA) coupled with a top‐view optical microscope. The surface energies of PBA–UPy4.0 and PBA–UPy7.2 (with mole percentages of UPy 4.0% and 7.2%, respectively) are estimated to be 45–56 mJ m^?2 under dry condition by contact angle measurements using a three probe liquid method and also by contact and adhesion mechanics tests, as compared to the reported literature value of 31–34 mJ m^?2 for PBA, an increase that is attributed to the strong UPy–UPy H‐bonding interactions. The adhesion strengths of PBA–UPy polymers depend on the UPy content, contact time, temperature and humidity level. Fractured PBA–UPy films can fully recover their self‐adhesion strength to 40, 81, and 100% in 10 s, 3 h, and 50 h, respectively, under almost zero external load. The fracture patterns (i.e., viscous fingers and highly “self‐organized” parallel stripe patterns) have implications for fabricating patterned surfaces in materials science and nanotechnology. These results provide new insights into the fundamental understanding of adhesive mechanisms of multiple hydrogen‐bonding polymers and development of novel self‐healing and stimuli‐responsive materials.